Summary
This paper presents novel methodological approaches to characterise the temporal relationship between surface and subsurface soil moisture using time-series data. By incorporating lagged dependence into a distributed-lag nonlinear model framework, the authors identified periods of coupling and decoupling across multiple sites, revealing that soil moisture decoupling occurs across a broader range of conditions than previously recognised. The findings have implications for improving the accuracy of depth-integrated soil moisture estimates derived from remote-sensing data.
UK applicability
The methodology developed here could enhance UK soil moisture monitoring and hydrological modelling, particularly for rainfed agricultural systems and water management applications. However, the applicability depends on the specific soil types, climatic conditions, and measurement protocols used in the original study sites.
Key measures
Lagged dependence between surface and subsurface soil moisture; distributed-lag nonlinear model (DLNM) functional relations and lag structures; coupled/decoupled soil moisture ranges identified via loess residual analysis
Outcomes reported
The study developed and tested methods using distributed-lag nonlinear modelling (DLNM) to identify periods when surface and subsurface soil moisture conditions are coupled or decoupled. The research quantified a range of decoupled soil moisture values and found that decoupling is not limited to dry conditions.
Topic tags
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